Antimicrobial potential of a ponericin-like peptide isolated from Bombyx mori L. hemolymph in response to Pseudomonas aeruginosa infection

Synthesis, characterization and application of silk sericin-based silver nanocomposites for antibacterial and food coating solutions

The rising demand for fresh and safe food is driving advancements in preservation technologies, with nanoparticles offering a revolutionary solution. These particles extend shelf life, preserve nutritional value, and enhance food safety, aligning with present consumer expectations. This study explores the eco-friendly synthesis, characterization, and application of silk sericin-based silver nanoparticles (SS-AgNPs) for antibacterial and food coating purposes. Silk sericin, a byproduct of the silk industry, is typically discarded despite its valuable properties like biocompatibility, biodegradability, and antimicrobial activity. In this research, sericin from Bombyx mori cocoons was used as a reducing and stabilizing agent to synthesize SS-AgNPs. Characterization was performed using UV-vis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and dynamic light scattering (DLS). Antibacterial tests confirmed the efficacy of SS-AgNPs against Pseudomonas sp. and Staphylococcus sp., while food coating trials on tomatoes significantly reduced weight loss and microbial contamination. Biocompatibility was further verified through hemolysis and MTT assays, confirming SS-AgNPs' safety for biomedical and food-related uses. This study underscores the potential to convert sericin waste into a valuable resource, promoting sustainability and increasing the commercial value of sericulture.

Multifunctional silver nanoparticle embedded eri silk cocoon scaffolds against burn wounds-associated infection

Antimicrobial wound dressings offer enhanced efficacy compared to conventional dressing platforms by limiting bacterial infections, expediting the healing process, and creating a barrier against additional wound contamination. The use of silk derived from silkworm cocoons in wound healing applications is attributed to its exceptional characteristics. Compared to mulberry silk, sericin from non-mulberry cocoons has higher water exchange mobility and moisture retention. Eri, a non-mulberry silkworm, is an unexplored source of silk with an eco-friendly nature of production where the natural life cycle of silkworms is not disrupted, and no moths are sacrificed. This work reports on an eri silk cocoon-based scaffold decorated with silver nanoparticles as a wound dressing material effective against burn-wound-associated multiple-drug-resistant bacteria. The UV-vis spectroscopy showed maximum absorbance at 448 nm due to the surface plasmon resonance of silver nanoparticles. FT-IR spectra exhibited the functional groups in the eri silk proteins accountable for the reduction of Ag+ to Ag0 in the scaffold. SEM-EDX analysis revealed the presence of elemental silver, and XRD analysis confirmed their particle size of 5.66-8.82 nm. The wound dressing platform showed excellent thermal stability and hydrophobicity, fulfilling the criteria of a standard waterproof dressing material, and anticipating the prevention of bacterial biofilm formation in chronic wounds. The scaffold was found to be effective against both Staphylococcus aureus (MTCC 87) and Pseudomonas aeruginosa (MTCC 1688) multiple-drug-resistant pathogens. Electron microscopy revealed the bacterial cell damage, suggesting its bactericidal property. The results further revealed that the scaffold was both hemocompatible and cytocompatible, suggesting its potential application in chronic wounds such as burns. As an outcome, this study presents a straightforward, cost-effective, and sustainable way of developing a multifunctional wound dressing platform, suggesting its significant therapeutic potential in clinical and biomedical sectors and facile commercialization.

Development of Aptamer-Functionalized Gold Nanoparticles as Probes in Point-of-Care Diagnostic Device for Rapid Detection of Multidrug-Resistant Bacteria in Bombyx mori L.

The sericulture industry suffers severe crop losses due to various silkworm diseases, necessitating the development of further technologies for rapid pathogen detection. Here, we report an all-in-one portable biosensor that combines conjugated gold nanoparticles (Au NPs) with an aptamer-based lateral flow assay (LFA) platform for the real-time analysis of Mammaliicoccus sp. and Pseudomonas sp. Our platform enables sample-to-answer naked eye detection within 5 min without any cross-reactivity with other representatives of the silkworm pathogenic bacterial group. This assay was based on the sandwich-type format using a bacteria-specific primary aptamer (Apt1) conjugated with 23 nm ± 1.27 nm Au NPs as a signal probe and another bacteria-specific secondary aptamer (Apt2)-coated nitrocellulose membrane as a capture probe. The hybridization between the signal probe and the capture probe in the presence of bacteria develops a red band in the test line, whose intensity is directly proportional to the bacterial concentration. Under the optimal experimental conditions, the visual limit of detection of the strip for Mammaliicoccus sp. and Pseudomonas sp. was 1.5 × 104 CFU/mL and 1.5 × 103 CFU/mL, respectively. Additionally, the performance of the LFA device was validated by using a colorimetric assay, and the results from the colorimetric assay are consistent with those obtained from the LFA. Our findings indicate that the developed point-of-care diagnostic device has significant potential for providing a cost-effective, scalable alternative for the rapid detection of silkworm pathogens.

How do physicochemical properties contribute to inhibitory activity of promising peptides against Zika Virus NS3 protease?

CONTEXT AND RESULTS

Flavivirus diseases' cycles, especially Dengue and Yellow Fever, can be observed all over Brazilian territory, representing a great health concern. Additionally, there are no drugs available in therapy. In this scenario, in silico methodologies were applied to obtain physicochemical properties, as well as to better understand the ligand-biological target interaction mode of 20 previously reported NS2B/NS3 protease inhibitors of Dengue virus. Since catalytic site of flavivirus hold similarities, such as the same catalytic triad (His51, Asp75 e Ser135), the ability of this series of molecules to fit in Zika NS3 domains can be achieved. We performed an exploratory data analysis, using statistical methodologies, such as PCA (Principal Component Analysis) and HCA (Hierarchical Component Analysis), to assist the comprehension of how physicochemical properties impact the interaction observed by the docking studies, as well as to build a correlation between the respective ranked characteristics. Based on these previous studies, peptides were selected for the dynamics simulations, which were useful to better understand the ligand-protein interactions. Information relating to, for instance, energy, ΔG, average number of hydrogen bonds and distance from Ser135 (one of the main amino acids in the catalytic pocket) were discussed. In this sense, peptides 15 (considering ΔG value and Hbond number), 7 (ΔG and energy) and 1, 6, 7 and 15 (the proximity to Ser135 throughout the dynamics simulation) were highlighted as promising. Those interesting results could contribute to future studies regarding Zika virus drug design, since this infection represents a great concern in neglected populations.

METHODS

The models were constructed in the ChemDraw software. The ligand parametrization was performed in the CHEM3D 17.0, UCSF Chimera. Docking simulations were carried out in the GOLD software, after the redocking validation. We used ASP as the function score. Additionally, for dynamics simulations we applied GROMACS software, exploring, mainly, free binding energy calculations. Exploratory analysis was carried out in Minitab 17.3.1 statistical software. Prior to the exploratory analysis, data of quantum chemical properties of the peptides were collected in Microsoft Excel spreadsheet and organized to obtain Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA).